Is the use of artificial intelligence the logical progression for driving efficiencies in the data centre?
Over recent years, the appetite for artificial intelligence (AI) has grown dramatically as businesses race to adopt the latest technology to get ahead. From retail to agriculture, AI is already being used in countless industries and it’s likely that this trend will continue.
According to research conducted by Infosys, 76% of IT decision makers believe that AI is a long-term strategic priority for innovation. So it’s not surprising that worldwide spending on cognitive and artificial intelligence systems is predicted to reach $57.6 billion in 2021, or that the technology is on the lips of media and influencers.
That said though, introducing technologies such as AI isn’t simple and doesn’t happen overnight. Data centres are vital for storing the data needed to power AI. So naturally, growth in this technology will require more from data centres which can be problematic, especially for those facilities already working at high capacity. This forces data centres to add more servers and hardware, which ultimately becomes complex to manage.
As with much technology underpinning business, many data centres run on inefficient legacy technology because companies tend to add to existing systems rather than optimising the existing system. All this puts extra pressure on data centres and intensifies long-standing issues. So, to keep pace, data centres will need to evolve.
Arguably, the most pressing of these issues is energy consumption as data centres now account for up to 6% of global electricity use. This is a concern for business costs and there is now increased pressure to take corporate responsibility for environmental concerns. Organisations including Greenpeace have been calling for tech companies to become more energy conscious for some time, and now they are honing in on data centres’ carbon footprint.
More data centres are moving to renewable energy sources, although this isn’t feasible for many – particularly smaller ones. Switching to renewable energy only addresses part of the problem, and as the demand for computing power continues to grow all options should be explored.
AI offers opportunities to improve efficiency and reduce energy consumption by using existing data and real-time monitoring. With AI, workloads can be distributed across servers to maximise productivity and solve network congestion issues. AI can also be used to control the data centre environment in real-time, such as cooling systems, to reduce energy consumption. Google is already implementing AI to monitor the data centre environment and reported that DeepMind AI was responsible for reducing Google’s data centre cooling bill by 40%.
Step up security
Another critical area under pressure in the modern data centre is security. In the cybersecurity battle, the stakes for data centres are particularly high. They’re highly complex infrastructures and have extensive levels of encryption, so preventing data breaches in an ever-evolving IT landscape requires constant vigilance.
The solution again may lie in AI. Implementing AI systems can offer a more flexible and sophisticated solution to data security as well as the possibility of reducing reliance on human intervention. The nature of AI allows it to adapt far more quickly than humans as well reducing the man-hours spent on round-the-clock monitoring issues and decrease the risk of human error.
With all these data centre opportunities unlocked by AI, the concept of a human-free data centre is closer than many imagine. Some companies like Litbit are already trialling-AI driven robots to assist with data centre management and hardware maintenance further cementing the ties between AI and data centre.
The demand for AI won’t be slowing down any time soon. This will only increase the demand for the physical space to store the huge quantity of data needed to run AI, which will, of course, increase the demand for data centres. Data is the lifeblood of AI meaning the increase in data centre capacity in the future will be mandatory.
Getting a flexible, future-defined data centre infrastructure in place is crucial to prepare for AI. Once the foundation is in place, servers can learn from the data they process, creating the cycle that improves AI and data centre ecosystems endlessly.
By Guy England, Director, Lenovo DCG